Esempio n. 1
0
# -*- coding: utf-8 -*-
"""
Created on Tue Jul 30 17:09:37 2019

@author: dori
"""
import sys
sys.path.append('..')
from READ import slice_data
from READ import icon150heights
from READ import read_variables
from statistic import hist_and_plot

pamtra = read_variables(
    path='/work/develop/pamtraICON/comparison/data/pamtra/',
    hydroset='all_hydro',
    suffix='pamtra_icon.h5',
    varlist=['Hgt', 'Z10', 'Z35', 'Z94'],
    minhour=6.0)
radar = read_variables(
    path='/work/develop/pamtraICON/comparison/data/radar/',
    hydroset='',
    suffix='radar.h5',
    varlist=['Hgt', 'Z10', 'Z35', 'Z94', 'quality_x', 'quality_w'],
    minhour=6.0)

radarw = slice_data(radar, 'quality_w', maxvalue=8192)
radarx = slice_data(radar, 'quality_x', maxvalue=8192)
#radarxw = slice_data(radarw, 'quality_x', maxvalue=8192)

#%% Z CFAD Height
lognormrule = True
Esempio n. 2
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"""
Created on Thu Sep  5 16:35:02 2019

@author: dori
"""

import sys
sys.path.append('..')
from READ import slice_data
from READ import read_variables
from statistic import hist_and_plot
import matplotlib.pyplot as plt
import netCDF4

pamtra = read_variables(path='/work/develop/pamtraICON/comparison/data/pamtra/',
                        hydroset='all_hydro', suffix='pamtra_icon.h5', pamtra=True,
                        varlist=['Z10', 'Z35', 'Z94', 'T',
                                 'W10', 'W35', 'W94'], minhour=6.0)

ice = read_variables(path='/work/develop/pamtraICON/comparison/data/pamtra/',
                        hydroset='only_ice', suffix='pamtra_icon.h5', pamtra=True,
                        varlist=['Z10', 'Z35', 'Z94', 'T',
                                 'W10', 'W35', 'W94'], minhour=6.0)

snow = read_variables(path='/work/develop/pamtraICON/comparison/data/pamtra/',
                        hydroset='only_snow', suffix='pamtra_icon.h5', pamtra=True,
                        varlist=['Z10', 'Z35', 'Z94', 'T',
                                 'W10', 'W35', 'W94'], minhour=6.0)

radar = read_variables(path='/work/develop/pamtraICON/comparison/data/radar/',
                       hydroset='', suffix='radar_regrid.h5', minhour=6.0,
                       varlist=['Z10', 'Z35', 'Z94', 'T',
Esempio n. 3
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from READ import read_variables
from statistic import hist_and_plot

varlist = [
    'Hgt', 'P', 'T', 'RH', 'Z10', 'Z35', 'Z94', 'N10', 'N35', 'N94', 'QI',
    'QC', 'QG', 'QH', 'QR', 'QS', 'QNI', 'QNC', 'QNG', 'QNH', 'QNR', 'QNS'
]

hydro = [
    'QS', 'QI', 'QC', 'QG', 'QH', 'QR', 'QNS', 'QNI', 'QNC', 'QNG', 'QNH',
    'QNR'
]

pamtra = read_variables(
    path='/work/develop/pamtraICON/comparison/data/pamtra/',
    hydroset='all_hydro',
    suffix='pamtra_icon.h5',
    varlist=varlist,
    minhour=6.0)

data = pamtra.dropna(subset=['DWRxk'])
data['RI'] = data['QI'] / data['QNI']
data['RS'] = data['QS'] / data['QNS']
data['RC'] = data['QC'] / data['QNC']
data['RR'] = data['QR'] / data['QNR']
data['RG'] = data['QG'] / data['QNG']
data['RH'] = data['QH'] / data['QNH']

data[hydro] = np.log10(data[hydro])

data['QNS'][data['QNS'] == -np.inf] = -302
data['QNI'][data['QNI'] == -np.inf] = -289
Esempio n. 4
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pam = pd.read_hdf('../data/pamStatCTTmaxDWR.h5', key='stat')
pam.index = pd.to_datetime(pam.index, unit='s')
pam = pam.resample('1s').nearest(limit=1)

ixi = pd.date_range(start='2015-11-11', end='2016-1-4', freq='9s')
icon.reindex(ixi)
icon = icon.resample(freq).apply(np.nansum)

ixp = pd.date_range(start='2015-11-11', end='2016-1-4', freq='1min')
pluvio.reindex(ixp)
pluvio = pluvio.resample(freq).apply(np.nansum)

pamtra = read_variables(
    path='/work/develop/pamtraICON/comparison/data/pamtra/',
    hydroset='all_hydro',
    suffix='pamtra_icon.h5',
    pamtra=True,
    minhour=6.0,
    attHYD=True,
    varlist=['Z10', 'Z35', 'Z94', 'T', 'unixtime', 'H10', 'H35', 'H94'])

radar = read_variables(
    path='/work/develop/pamtraICON/comparison/data/radar/',
    hydroset='',
    suffix='radar_regrid.h5',
    minhour=6.0,
    varlist=['Z10', 'Z35', 'Z94', 'T', 'unixtime', 'quality_x', 'quality_w'])

radar = read_variables(
    path='/work/develop/pamtraICON/comparison/data/radar/',
    hydroset='',
    suffix='radar.h5',
Esempio n. 5
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mrr = pd.read_hdf(mrrfile, key='stat')
mrr = mrr.resample(freq).apply(np.nansum)

ixi = pd.date_range(start='2015-11-11', end='2016-1-4', freq='9s')
icon.reindex(ixi)
icon = icon.resample(freq).apply(np.nansum)

ixp = pd.date_range(start='2015-11-11', end='2016-1-4', freq='1min')
pluvio.reindex(ixp)
pluvio = pluvio.resample(freq).apply(np.nansum)

pamtra = read_variables(
    path='/work/develop/pamtraICON/comparison/data/pamtra/',
    hydroset='all_hydro',
    suffix='pamtra_icon.h5',
    pamtra=True,
    minhour=6.0,
    varlist=[
        'Z10', 'Z35', 'Z94', 'W10', 'W35', 'W94', 'T', 'unixtime', 'P', 'RH',
        'QNR', 'QR', 'QG', 'QI', 'QS', 'QH', 'QC', 'S35', 'V10', 'V35', 'V94'
    ])

pamtra['Q'] = pamtra['QR'] + pamtra['QG'] + pamtra['QI'] + pamtra[
    'QS'] + pamtra['QH'] + pamtra['QC']
pamtra['R/Q'] = pamtra['QR'] / pamtra['Q']

#ice = read_variables(path='/work/develop/pamtraICON/comparison/data/pamtra/',
#                        hydroset='only_ice', suffix='pamtra_icon.h5', pamtra=True,
#                        varlist=['Z10', 'Z35', 'Z94', 'T',
#                                 'V10', 'V35', 'V94', 'unixtime',
#                                 'W10', 'W35', 'W94'], minhour=6.0)
#